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• Hardware Platform (Jetson / GPU)
• DeepStream Version
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only)
• Issue Type( questions, new requirements, bugs)
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
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I’m noticing phantom detections in all cluster-modes != 0 at high pre-cluster-threshold of 0.5.
I took a 50 seconds snip off of this video Morning Meeting and Warm up - Sysco Eastern WI - Capstone Logistics - YouTube and did run inference on it using the deepstream-test3.py sample
Leave deepstream-test3.py unchanged but apply these changes to dstest3_pgie_config.txt. IMHO all “normal” and legit changes:
diff --git a/apps/deepstream-test3/dstest3_pgie_config.txt b/apps/deepstream-test3/dstest3_pgie_config.txt index a6a797f..16e3e65 100644 --- a/apps/deepstream-test3/dstest3_pgie_config.txt +++ b/apps/deepstream-test3/dstest3_pgie_config.txt @@ -59,23 +59,24 @@ [property] gpu-id=0 +workspace-size=600 net-scale-factor=0.0039215697906911373 -model-file=../../../../samples/models/Primary_Detector/resnet10.caffemodel -proto-file=../../../../samples/models/Primary_Detector/resnet10.prototxt -model-engine-file=../../../../samples/models/Primary_Detector/resnet10.caffemodel_b1_gpu0_int8.engine -labelfile-path=../../../../samples/models/Primary_Detector/labels.txt -int8-calib-file=../../../../samples/models/Primary_Detector/cal_trt.bin +model-file=../../../../samples/models/Primary_Detector_Nano/resnet10.caffemodel +proto-file=../../../../samples/models/Primary_Detector_Nano/resnet10.prototxt +model-engine-file=../../../../samples/models/Primary_Detector_Nano/resnet10.caffemodel_b3_gpu0_fp16.engine +labelfile-path=../../../../samples/models/Primary_Detector_Nano/labels.txt force-implicit-batch-dim=1 -batch-size=1 +batch-size=3 process-mode=1 model-color-format=0 -network-mode=1 +network-mode=2 num-detected-classes=4 interval=0 gie-unique-id=1 output-blob-names=conv2d_bbox;conv2d_cov/Sigmoid +cluster-mode=3 [class-attrs-all] -pre-cluster-threshold=0.2 +pre-cluster-threshold=0.5 eps=0.2 group-threshold=1
With this setup you will notice a single shot person detection at frame 785 after about 10 seconds of no detection. With the same pre-cluster-threshold but cluster-mode=0 there is no such a phantom.
You might say, who gives a f… on such a single event. I would like to point out, that my use case is to detect possible collisions beforehand. As you can see, there is a long drive along an aisle in a warehouse. The algorithm shoots out of the sudden with a detection rectangle, which renders to an approximate distance of 1 m to the “person” ahead (aka ghost in this case). This would definitely have to result in a full-brake event. For nothing.
I need the “confidence” value, otherwise I would be OK to go with cluster-mode=0